The core idea of this approach is to estimate the influence spread \(I(S)\)  of a given user set \(S\)  by using the Monte Carlo (MC) simulations of the diffusion process [1]}, [2]}, [3]}. Specifically, for a given user set \(S\) , we simulate the randomized diffusion process with \(S\)  for \(R\)  times. Each time we count the number of active users after the diffusion ends, and then take the average of these counts over the \(R\)  times.
